Juvenile localized scleroderma: Clinical and epidemiological features in 750 children. An international study

Objective. Juvenile localized scleroderma (JLS) includes a number of conditions often grouped together. With the long-term goal of developing uniform classification criteria, we studied the epidemiological, clinical and immunological features of children with JLS followed by paediatric rheumatology and dermatology centres. Methods. A large, multicentre, multinational study was conducted by collecting information on the demographics, family history, triggering environmental factors, clinical and laboratory features, and treatment of patients with JLS. Results. Seven hundred and fifty patients with JLS from 70 centres were enrolled into the study. The disease duration at diagnosis was 18 months. Linear scleroderma (LS) was the most frequent subtype (65%), followed by plaque morphea (PM) (26%), generalized morphea (GM) (7%) and deep morphea (DM) (2%). As many as 15% of patients had a mixed subtype. Ninety-one patients (12%) had a positive family history for rheumatic or autoimmune diseases; 100 (13.3%) reported environmental events as possible trigger. ANA was positive in 42.3% of the patients, with a higher prevalence in the LS-DM subtype than in the PM-GM subtype. Scl70 was detected in the sera of 3% of the patients, anticentromere antibody in 2%, anti-double-stranded DNA in 4%, anti-cardiolipin antibody in 13% and rheumatoid factor in 16%. Methotrexate was the drug most frequently used, especially during the last 5 yr. Conclusion. This study represents the largest collection of patients with JLS ever reported. The insidious onset of the disease, the delay in diagnosis, the recognition of mixed subtype and the better definition of the other subtypes should influence our efforts in educating trainees and practitioners and help in developing a comprehensive classification system for this syndrome. © 2006 Oxford University Press.

GDP 4.0 transfer to SGP 3.0 for SCIAMACHY no2 column processing: Verification with SDOAS / GDOAS prototype algorithms and delta-validation with NDACC / UV-visible network data

Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

Blade design and forming for fans using finite elements

The necessity of adapting the standardized fan models to conditions of higher temperature has emerged due to the growth of concerning referring to the consequences of the gas expelling after the Mont Blanc tunnel accident in Italy and France, where even though, with 100 fans in operation, 41 people died. However, since then, the defied solutions have pointed to aerodynamic disadvantages or have seemed nonappropriate in these conditions. The objective of this work is to present an alternative to the market standard fans considering a new technology in constructing blades. This new technology introduces the use of the stainless steel AISI 409 due to its good adaptation to temperatures higher than 400°C, particularly exposed to temperatures of gas exhaust from tunnels in fire situation. Furthermore, it presents a very good resistance to corrosion and posterior welding and pressing, due to its alloyed elements. The innovation is centered in the process of a deep drawing of metallic shells and posterior welding, in order to keep the ideal aerodynamic superficies for the fan ideal performance. On the other hand, the finite element method, through the elasto-plastic software COSMOS permitted the verification of the thickness and structural stability of the blade in relation to the aerodynamic efforts established in the project. In addition, it is not advisable the fabrication of blades with variable localized thickness not even, non-uniform ones, due to the verified concentration of tensions and the difficulties observed in the forming. In this way, this study recommends the construction of blades with uniform variations of thickness. © 2007 Springer.

Comparative analysis of synchronization algorithms based on PLL, RDFT and Kalman Filter

This paper discusses the main characteristics and presents a comparative analysis of three synchronization algorithms based respectively, on a Phase-Locked Loop, a Kalman Filter and a Discrete Fourier Transform. It will be described the single and three-phase models of the first two methods and the single-phase model of the third one. Details on how to modify the filtering properties or dynamic response of each algorithm will be discussed in terms of their design parameters. In order to compare the different algorithms, these parameters will be set for maximum filter capability. Then, the dynamic response, during input amplitude and frequency deviations will be observed, as well as during the initialization procedure. So, advantages and disadvantages of all considered algorithms will be discussed. ©2007 IEEE.

Pitch detection algorithms based on zero-cross rate and autocorrelation function for musical notes

This paper discusses two pitch detection algorithms (PDA) for simple audio signals which are based on zero-cross rate (ZCR) and autocorrelation function (ACF). As it is well known, pitch detection methods based on ZCR and ACF are widely used in signal processing. This work shows some features and problems in using these methods, as well as some improvements developed to increase their performance. © 2008 IEEE.

Evaluating genetic algorithms with different population structures on a lot sizing and scheduling problem

This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.

The role of coarse intermetallics in the localized corrosion behaviour of AA 2024-T3 in low concentrated chloride media

Aluminium alloy (AA) 2024-T3 is an important engineering material due to its widespread use in the aerospace industry. However, it is very prone to localized corrosion attack in chloride containing media, which has been mainly associated to the presence of coarse intermetallics (IMs). In this work the corrosion behaviour of aluminium alloy 2024-T3 in low concentrated chloride media was investigated using microscopy and electrochemical methods. SEM observations have shown that intermetallics with the same nominal composition present heterogeneous reaction rates, and that both types of coarse IMs normally found in the AA 2024-T3 microstructure corrode. Moreover, EDS analyses have shown important compositional changes in the corroded IMs, evidencing the selective corrosion of their more active constituents and the onset of an intense oxygen peak, irrespective to the IM nature. TEM/EDS observations on non-corroded samples have evidenced the heterogeneous composition within the IMs. On the other hand, the results of the electrochemical investigations, in accordance with the SEM/EDS observations, have evidenced that IMs corrosion dominates the electrochemical response of the alloy during the first hours of immersion in the test electrolyte. © 2009 by NACE International.

Optimal trajectory and solution of the inverse kinematics of a robotic manipulator by genetic algorithms

This paper presents the generation of optimal trajectories by genetic algorithms (GA) for a planar robotic manipulator. The implemented GA considers a multi-objective function that minimizes the end-effector positioning error together with the joints angular displacement and it solves the inverse kinematics problem for the trajectory. Computer simulations results are presented to illustrate this implementation and show the efficiency of the used methodology producing soft trajectories with low computing cost. © 2011 Springer-Verlag Berlin Heidelberg.

Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.

Vectorized algorithms for quadtree construction and descent

This paper presents vectorized methods of construction and descent of quadtrees that can be easily adapted to message passing parallel computing. A time complexity analysis for the present approach is also discussed. The proposed method of tree construction requires a hash table to index nodes of a linear quadtree in the breadth-first order. The hash is performed in two steps: an internal hash to index child nodes and an external hash to index nodes in the same level (depth). The quadtree descent is performed by considering each level as a vector segment of a linear quadtree, so that nodes of the same level can be processed concurrently. © 2012 Springer-Verlag.

The assessment of the quality of sugar using electronic tongue and machine learning algorithms

The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system along with established techniques of supervised learning leads to the correct classification of sugar samples according to their qualities. In this paper, we offer two new real, public and non-encoded sugar datasets whose attributes were automatically collected using an electronic tongue, with and without pH controlling. Moreover, we compare the performance achieved by several established machine learning methods. Our experiments were diligently designed to ensure statistically sound results and they indicate that k-nearest neighbors method outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further comparison. © 2012 IEEE.

Use of algorithms for semi-automatic quantification of pulmonary fibrosis and emphysema

Obtaining a semi-automatic quantification of pathologies found in the lung, through images of high resolution computed tomography (HRCT), is of great importance to aid in medical diagnosis. Paraccocidioidomycosis (PCM) is a systemic disease that affects the lung and even after effective treatment leaves sequels such as pulmonary fibrosis and emphysema. It is very important to the area of tropical diseases that the lung injury be quantified more accurately. In this stud, we propose the development of algorithms in computational environment Matlab® able to objectively quantify lung diseases such as fibrosis and emphysema. The program consists in selecting the region of interest (ROI), and through the use of density masks and filters, obtaining the lesion area quantification in relation to the healthy area of the lung. The proposed method was tested on 15 exams of HRCT of patients with confirmed PCM. To prove the validity and effectiveness of the method, we used a virtual phantom, also developed in this research. © 2013 Springer-Verlag.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Analysis of localized muscle fatigue in elderly women with and without a history of falls using electromyographic signal frequency parameters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)